After the completion of the human genome sequence decoding project, proteome analysis, in which proteins responsible for actual life phenomena are analyzed, has drawn attention. The reason for this is that it is believed that direct analysis of proteins leads to finding of causes for diseases, drug discovery, and tailor-made medical care. Another reason why proteome analysis has drawn attention is, for example, that transcriptome analysis, in other words, analysis of expression of RNA that is a transcription product, does not allow protein expression to be satisfactorily predicted, and that genome information hardly provides a modified domain or conformation of a posttranslationally-modified protein.
The number of types of protein to undergo proteome analysis has been estimated to be several tens of thousands per cell, whereas the amount of expression, in terms of the number of molecules, of each protein has been estimated to range from approximately one hundred to one million per cell. Considering that cells in which each of the proteins is expressed are only part of a living organism, the amount of expression of the protein in the living organism is significantly small. Further, since an amplification method used in the genome analysis cannot be used in the proteome analysis, a detection system in the proteome analysis is effectively limited to a high-sensitivity type of mass spectrometry.
A typical procedure of the proteome analysis is as follows:    (1) Separation and refinement by using two-dimensional electrophoresis or high performance liquid chromatography (HPLC)    (2) Trypsin digestion of separated and refined protein    (3) Mass spectrometry of the thus obtained peptide fragment compound    (4) Protein identification by cross-checking protein database
The method described above is called a peptide mass fingerprinting method (PMF). In PMF-based mass spectrometry, it is typical that MALDI is used as an ionization method and a TOF mass spectrometer is used as a mass spectrometer.
In another method for performing the proteome analysis, MS/MS measurement is performed on each peptide by using ESI as an ionization method and an ion trap mass spectrometer as a mass spectrometer, and consequently the resultant product ion list may be used in a search process. In the search process, a proteome analysis search engine MASCOT® developed by Matrix Science Ltd. or any other suitable software is used. In the method described above, although the amount of information is larger and more complicated than that in a typical PMF method, the attribution of a continuous amino acid sequence can also be identified, whereby more precise protein identification can be performed than in a typical PMF method.
In addition to the above, examples of related technologies having drawn attention in recent years may include a method for identifying a protein and a peptide fragment based on high resolution mass spectrometry using a Fourier transform mass spectrometer, a method for determining an amino acid sequence through computation by using a peptide MS/MS spectrum and based on mathematical operation called De novo sequencing, a pre-processing method in which (several thousand of) cells of interest in a living tissue section are cut by using laser microdissection, and mass spectrometry-based methods called selected reaction monitoring (SRM) and multiple reaction monitoring (MRM) for quantifying a specific peptide contained in a peptide fragment compound.
On the other hand, in pathologic inspection, for example, a specific antigen in a tissue needs to be visualized. A method mainly used in such pathologic inspection has been so far a method for staining a specific antigen protein by using immunostaining method. In the case of breast cancer, for example, what is visualized by using immunostaining method is ER (estrogen receptor expressed in a hormone dependent tumor), which is a reference used to judge whether hormone treatment should be given, and HER2 (membrane protein seen in a progressive malignant cancer), which is a reference used to judge whether Herceptin should be administered. Immunostaining method, however, involves problems of poor reproducibility resulting from antibody-related instability and difficulty in controlling the efficiency of an antigen-antibody reaction. Further, when demands for such functional diagnoses grow in the future, and, for example, more than several hundreds of types of protein need to be detected, the current immunostaining method cannot meet the requirement.
Still further, in some cases, a specific antigen may be required to be visualized at a cell level. For example, since studies on tumor stem cells have revealed that only fraction in part of a tumor tissue, after heterologous transplantation into an immune-deficient mouse, forms a tumor, for example, it has been gradually understood that the growth of a tumor tissue depends on the differentiation and self-regenerating ability of a tumor stem cell. In a study of this type, it is necessary to observe the distribution of an expressed specific antigen in individual cells in a tissue instead of the distribution in the entire tissue.
As described above, visualization is demanded of an expressed protein, for example in a tumor tissue, exhaustively on a cell level, and a candidate analysis method for the purpose is measurement based on secondary ion mass spectrometry (SIMS) represented by time-of-flight secondary ion mass spectrometry (TOF-SIMS). In this SIMS-based measurement, two-dimensional, high spatial resolution mass spectrometry information can be obtained. Also, the distribution of each peak in a mass spectrum is readily identified. As a result, the protein corresponding to the spatial distribution of the mass spectrum is identified in a more reliable manner in a shorter period than in related art. The entire data is therefore in some cases taken as three-dimensional data (positional information is stored in the xy plane, and spectral information corresponding to each position is stored along the z-axis direction) for subsequent data processing.
SIMS is a method for producing a mass spectrum at each spatial point by irradiating a sample with a primary ion beam and detecting secondary ions emitted from the sample. For example, in TOF-SIMS, a mass spectrum at each spatial point can be produced based on the fact that the time of flight of each secondary ion depends on the mass M and the amount of charge of the ion. However, since ion detection is a discrete process, and when the number of detected ions is not large, the influence of noise is not negligible. Noise reduction is therefore performed by using a variety of methods.
Among a variety of noise reduction methods, PTL 1 proposes a method for effectively performing noise reduction by using wavelet analysis to analyze two or more two-dimensional images and correlating the images with each other. Another noise reduction method is proposed in NPL 1, in which two-dimensional wavelet analysis is performed on SIMS images in consideration of a stochastic process (Gauss or Poisson process).
The “at a cell level” described above means a level that allows at least individual cells to be identified. While the diameter of a large cell, such as a nerve cell, is approximately 50 μm, that of a typical cell ranges from 10 to 20 μm. To acquire a two-dimensional distribution image at a cell level, the spatial resolution therefore needs to be 10 μm or smaller, preferably 5 μm or smaller, more preferably 2 μm or smaller, still more preferably 1 μm or smaller. The spatial resolution can be determined, for example, from a result of line analysis of a knife-edge sample. In general, the spatial resolution is determined based on a typical definition below: “the distance between two points where the intensity of a signal associated with a substance located on one of the two sides of the contour of the sample is 20% and 80%, respectively.”